About

Richard Mayer is a Distinguished Professor in the Department of Psychology at the University of California, Santa Barbara. His areas of specialization include human learning, problem-solving, educational psychology, human-computer interaction, multimedia learning, and mathematical and scientific reasoning. Mayer's work focuses on understanding how people learn and solve problems, particularly through the use of multimedia and technology, contributing significantly to the fields of educational psychology and applied linguistics. His research aims to improve instructional methods and learning outcomes by exploring the cognitive processes involved in learning and reasoning.

Research topics

• Artificial Intelligence
• Computer Science
• Psychology
• Mathematics education
• Multimedia
• Computer graphics (images)
• Human–computer interaction

Selected publications

• Emotional reactions to performance feedback as measured by self-reports and automatic facial recognition.

  Journal of Educational Psychology · 2026-05-11

  article
  PublisherDOI

• Role of Race and Gender of Pedagogical Agents in Multimedia Learning

  Journal of Educational Computing Research · 2025-02-25 · 7 citations

  articleOpen access

  Do students learn from video lessons presented by pedagogical agents of different racial and gender types equivalently to those delivered by a real human instructor? How do the race and gender of these agents impact students’ learning experiences and outcomes? In this between-subject design study, college students were randomly assigned to view a six 9-minute video lesson on chemical bonds, presented by pedagogical agents varying in gender (male, female) and race (Asian, Black, White), or to view the original lesson with a real human instructor. In comparing learning with a human instructor versus with a pedagogical agent of various races and genres, ANOVAs revealed no significant differences in learning outcomes (retention and transfer scores) or learner emotions, but students reported a stronger social connection with the human instructor over pedagogical agents. Students reported stronger positive emotions and social connections with female agents over male agents. Additionally, there was limited evidence of a race-matching effect, with White students showing greater positive emotion while learning with pedagogical agents of the same race. These findings highlight the limitations of pedagogical agents compared to human instructors in video lessons, while partially reflecting gender stereotypes and intergroup bias in instructor evaluations.

  PublisherOA PDFDOI

• Handbook of Research on Learning and Instruction

  2025-10-28 · 1 citations

  book1st authorCorresponding
  PublisherDOI

• Maximizing the benefits of student-generated drawing for real-world problem solving

  Contemporary Educational Psychology · 2025-04-14 · 4 citations

  articleOpen accessSenior author

  • College students were asked to draw while solving real-world problems. • Mathematical drawing instructions led to fewer situational elements in drawings. • Providing drawing support led to more accurate drawings. • More accurate drawings with fewer situational elements led to better performance. • Mathematical drawing instructions with support improved performance. Solving real-world problems is a challenge for many students. The two-pathway model of student-generated drawing for real-world problem solving states that problem-solving performance is maximized when students make drawings that are (1) accurate and (2) in mathematical format. We investigated how drawing accuracy and problem-solving performance are affected by presence or absence of drawing support in the form of providing thumbnail representations of the key elements to be used in the drawing (intended to enhance drawing accuracy) and providing mathematical drawing instructions to create schematic representations (intended to prime mathematical format in drawings) or situational drawing instructions to create pictorial representations (intended to prime drawings with extraneous situational elements). In a 2 x 2 between-subjects experiment with drawing support (supported drawing or unsupported drawing) and drawing instructions (situational drawing instructions or mathematical drawing instructions) as factors, 112 undergraduate students were randomly assigned to one of four drawing conditions. In line with the two-pathway model, we found that students provided with drawing support and mathematical drawing instructions outperformed those in other conditions on solving real-world problems. Based on path analyses, this effect was attributed to higher drawing accuracy and fewer extraneous situational elements in their drawings. Results support the two-pathway model of how student-generating drawing can support real-world problem solving.

  PublisherDOI

• Learner-Generated and Instructor-Provided Graphic Organizers as Aids to Learning from Text: A Meta-Analysis

  Educational Psychology Review · 2025-11-18 · 1 citations

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  PublisherDOI

• Cloze tests as retrieval practice activities: evaluating their integration with audience response systems in K-12 schools

  Instructional Science · 2025-08-27

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  PublisherDOI

• Introduction to Research on Instruction

  2025-10-28

  book-chapterSenior author

  “And so everywhere the teaching must agree with the psychology, but need not necessarily be the only kind of teaching that would so agree; for many diverse methods of teaching may equally well agree with psychological laws.”

  PublisherDOI

• Introduction to Research on Learning

  2025-10-28

  book-chapter1st authorCorresponding

  The psychology of subject matter is the scientific study of how people learn school subjects such as reading, writing, mathematics, and science (Mayer, 1999, 2004). Similarly, Discipline-Based Education Research (DBER) focuses on research on learning and teaching in specific disciplines, such as physics, biology, geoscience, and chemistry (Land, 2021; Singer et al., 2012). Although research on learning in academic content areas has a long history dating back to classic research by Huey (1908) on reading and Thorndike (1922) on arithmetic, much progress has been made, particularly in the past several decades. For this reason, the development of the psychology of subject matter or discipline-based research has been recognized as one of the major accomplishments of educational psychology (Alexander et al., 2012; Mayer, 2011). This first section of the Handbook provides a research-based overview of the exciting progress being made in our understanding of learning in subject areas and related academic skills. In addition to chapters on core subject areas such as reading, writing, mathematics, science, and history, we have expanded the section to include the subject areas of second language learning and the arts, as well as the hidden curriculum areas of critical thinking, self-regulated learning, and motivation, along with new chapters on emotion in academic learning and the neuroscience of learning.

  PublisherDOI

• Systematically Reviewing the Rigour of Immersive Virtual Reality Research in <scp>STEM</scp> Education: A Deep Dive Into Threats to Internal Validity

  Journal of Computer Assisted Learning · 2025-12-09 · 1 citations

  articleOpen accessSenior author

  ABSTRACT Background There have been many initiatives focused on implementing IVR in the classroom to either replace or supplement conventional instruction. The efficacy of these initiatives is often informed by IVR media comparison studies that examine the learning outcomes of students who learn academic content in IVR versus conventional media. However, the current methodological rigour of research on the use of IVR for learning in STEM education has not yet been established to ensure recommendations concerning its use in education are rooted in rigorous research studies. Objective The present review aimed to fill this gap in the literature by evaluating published journal articles, conference proceedings, and dissertations (between the years 2013 and 2023) related to IVR comparison studies in STEM education. Method The 44 articles were evaluated with respect to 13 internal validity controls (i.e., research design, justified sample size, group equivalence, attrition equivalence, operational definitions provided, matched dosage, matched timeframe, matched content, implementation fidelity, practice equivalence with dependent measures [ DMs ], equivalent DMs , interrater agreement for DM scoring and technical adequacy of DMs ). Results Results indicated there were no articles that explicitly met all 13 internal validity controls; the average number of control issues was 5.36. When articles were not penalised for missing information, 21 articles adhered to all internal validity controls. As can be seen when comparing these findings, the lack of methodological information was a glaring problem. Conclusion These findings indicate that there are both methodological problems and reporting problems in IVR media comparison research that need to be addressed to advance future IVR research. Recommendations for productively moving forward are discussed.

  PublisherOA PDFDOI

• From Generative AI to Extended Reality: Multidisciplinary Perspectives on the Challenges, Opportunities, and Future of Educational Computing

  Journal of Educational Computing Research · 2025-07-09 · 24 citations

  articleOpen access

  This editorial brings together the insights of fourteen members of the journal’s editorial board to critically examine the evolving landscape of educational computing. In an era marked by rapid technological advancements; from generative artificial intelligence to extended reality, this editorial explores the multidimensional challenges and opportunities these developments present for education. Drawing from multidisciplinary perspectives, the contributors collectively identify four thematic areas that demand sustained scholarly attention: (1) Equity, Inclusion, and the Digital Divide; (2) Ethics, Social Sustainability, and Well-being; (3) Instructional Design; and (4) Human-Computer Interaction in Educational Technologies. Each theme reflects a convergence of urgent concerns and transformative potential and is accompanied by forward-looking research questions that aim to shape the future agenda of the field. Together, the contributions highlight critical tensions and possibilities, offering a roadmap for researchers, practitioners, and policymakers committed to harnessing educational computing technologies in socially responsible, pedagogically sound, and human-centred ways.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: Multimedia learning principles for design-it-yourself online instruction of GIS concepts

  NSF · $146k · 2015–2018

• Collaborative Research: Using Artificial Intelligence to Transform Online Video Lectures into Effective and Inclusive Agent-Based Presentations

  NSF · $302k · 2022–2026

• Collaborative Research: Multimodal Affective Pedagogical Agents for Different Types of Learners

  NSF · $250k · 2018–2022

• Learning from Online Lectures in STEM: Using Multimedia Principles and Fostering Social Agency with Transparent Whiteboards

  NSF · $1.1M · 2016–2021

Frequent coauthors

• Logan Fiorella

  49 shared

• Roxana Moreno

  36 shared

• Mary Hegarty

  20 shared

• Deanne Adams

  University of California, Santa Cruz

  17 shared

• Fuxing Wang

  Central China Normal University

  17 shared

• Alyssa P. Lawson

  Landmark College

  16 shared

• Andrew T. Stull

  University of California, Santa Barbara

  15 shared

• Héctor R. Ponce

  13 shared